Wafer Defect Detection

_{Detection output on a sample optical lens image: defective regions are segmented and highlighted, with defect classification overlaid}

A C++ and OpenCV based computer vision system for automated detection and classification of defects on semiconductor wafer surfaces. Designed to segment defective regions from high-resolution wafer imagery and identify defect type.

Built as a proof-of-concept for inline inspection in semiconductor manufacturing workflows

Setup:

1. Clone the repository to your local machine.

git clone https://github.com/vetrivln/WaferDefectDetection

2. Add OpenCV to your project:

• Include directories -> opencv\build\include
• Library directories -> opencv\build\x64\vc16\lib
• Link .lib files -> opencv_world4xx.lib

3. Build and Run the project in Visual Studio.

Requirements:

• OS: Windows 10/11 (64 bit)
• Compiler: Visual Studio 2019/2022
• OpenCV: 4.x
• .NET: 4.7.2 or higher